Design of novel FLT-3 inhibitors based on dual-layer 3D-QSAR model and fragment-based compounds in silico

Kuei Chung Shih, Chun Yuan Lin, Hsiao Chieh Chi, Chrong Shiong Hwang, Ting Shou Chen, Chuan Yi Tang, Nai Wan Hsiao

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

FMS-like tyrosine kinase 3 (FLT-3) is strongly correlated with acute myeloid leukemia, but no FLT-3-inhibitor cocomplex structure is available to assist the design of therapeutic inhibitors. Hence, we propose a dual-layer 3D-QSAR model for FLT-3 that integrates the pharmacophore, CoMFA, and CoMSIA. We then coupled the model with the fragment-based design strategy to identify novel FLT-3 inhibitors. In the first layer, the previously established model, Hypo02, was evaluated in terms of its correlation coefficient (r), RMS, cost difference, and configuration cost, with values of 0.930, 1.24, 106.45, and 16.44, respectively. Moreover, Fischer's cross-validation test of data generated by Hypo02 yielded a 98% confidence level, and the validation of the testing set yielded a best r value of 0.87. The features of Hypo02 were separated into two parts and then used to screen the MiniMaybridge fragment compound database. Nine novel FLT-3 inhibitors were generated in this layer. In the second layer, Hypo02 was subjected to an alignment rule to generate CoMFA-and CoMSIA-based models, for which the partial least-squares validation method was utilized. The values of q 2, r 2, and predictive r 2 were 0.58, 0.98, and 0.76, respectively, derived from the CoMFA model with steric and electrostatic fields. The CoMSIA model with five different fields yielded values of 0.54, 0.97, and 0.76 for q 2, r 2, and predictive r 2, respectively. The CoMFA and CoMSIA models were used to constrain 3D structures of the nine novel FLT-3 inhibitors. This dual-layer 3D-QSAR model constitutes a valuable tool to easily and quickly screen and optimize novel potential FLT-3 inhibitors for the treatment of acute myeloid leukemia.

Original languageEnglish
Pages (from-to)146-155
Number of pages10
JournalJournal of Chemical Information and Modeling
Volume52
Issue number1
DOIs
Publication statusPublished - 2012 Jan 23

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Computer Science Applications
  • Library and Information Sciences

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